Spectrum sensing is needed in cognitive radios to find empty slots in the radio spectrum which can subsequently be used in an opportunistic manner. Traditionally radio spectrum is divided between different radio systems in a manner that strictly allocates a specific band to a specific system. This strict allocation will be changing to a more flexible spectrum utilization at least in some frequency bands in the future. Primary users are those operating within the more formal networks such as hierarchical networks (e.g., WLAN or cellular such as GSM, GERAN, UTRAN and E-UTRAN) and ad hoc networks (e.g., WiFi). Secondary users are those operating outside the structure of the formal networks. Since essentially all spectrum in crowded areas that is useable by mobile terminals is allocated to some formal network or another, the secondary users find and utilize portions of the existing networks' spectrum in an opportunistic manner. Consequently, two related obstacles face the secondary user: it must not interfere with the primary users, and it must somehow find those portions of the spectrum not currently in use by any of the formal networks. For this latter reason the secondary users are generally referred to as cognitive users; they must be spectrum-aware rather than simply using the radio resources allocated by some access node controlling a cell of users.
The secondary user/cognitive radio therefore utilizes or exploits a free region of spectrum for its own transmissions, outside control of the formal networks. By “free” is meant that the primary users/formal networks are not using the spectrum region in question when considering time, frequency and space. Alternatively there could be a band that is dedicated to several radio systems operating under a certain set of rules or policies. The common factor in any case is that the radio spectrum will have to be sensed somehow in order for the cognitive radio/secondary user to locate the free spectral band. This sensing has to at least take into account time, frequency and space.
The cognitive radio must be able to detect a primary user and avoid causing interference to it. Since cognitive radio is a wireless application, the cognitive radios have a limited power supply and so an important consideration in spectrum sensing is to minimize power usage. It is not inconsistent that the actual mobile terminals operating within the formal network(s) may act as the cognitive radios that also sense the spectrum quality, but the spectrum sensing task may also be undertaken by the cognitive radios operating wholly outside those networks' formal structure but utilizing the free radio resources opportunistically.
In theory the spectrum sensing task can be shared among various cognitive users in order to obtain savings in power consumption at the individual mobile users, to reduce the amount of data to be transmitted by those individual users, and consequently to facilitate the use of simpler sensing techniques in each individual user as compared to having individual terminals measure the entire spectrum in use across the network. One practical problem with collaboration is that the selection, control, and resultant handling of the collaborative nodes represent a control signaling overhead that occupies additional bandwidth because the collaborative nodes need to be controlled independently. Thus the potential spectrum savings by allocating bandwidth more efficiently in view of the spectrum sensing by the mobile terminals is offset, often more than offset, by the coordination required to get those mobile terminals to sense portions of the spectrum. This is particularly true when one tries to incorporate diversity into spectrum sensing so as to avoid the hidden node problem. Teachings relevant to collaborative spectrum sensing in a cognitive network may be seen more particularly at co-owned U.S. patent application Ser. No. 12/001,623, filed on Dec. 11, 2007 and entitled “Method and Apparatus to Select Collaborating Users in Spectrum Sensing”.
Being a very forward-looking technology at this stage of development, there is not a great volume of prior art in the spectrum sensing field. Three are detailed here. In a first proposal set forth by L. Luu and B. Daneshrad in a paper entitled An Adaptive Weaver Architecture Radio With Spectrum Sensing Capabilities to Relax RF Component Requirements [IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 25, No. 3, APRIL 2007], there is an adaptive Weaver receiver architecture containing a coarse spectrum sensing method. It uses variable LO-frequencies to enhance image-rejection. It is seen, however, as doing only a few frequency sweeps with simple power detection to measure the level of the signal at the image frequency, and so it is not seen as able to do a complete wide-band spectrum sensing operation.
A second paper by J. Laskar, et al, entitled Reconfigurable RFICs and Modules for Cognitive Radio [SIRF, 2006] presents a sensing method which is based on a coarse detection with wavelet transformation and then on a fine detection that uses an analog auto-correlation. It may in principle be suitable for the spectrum sensing task for cognitive radio applications at least with some properties. Few details are presented though and so it is difficult to find a workable solution for the specific cognitive radio problem. For example, this paper does not address the time-division of signals under detection in any way.
A third approach was presented by J. Yang, entitled Addressing the dynamic range problem in cognitive radios [Berkeley Wireless Research Center (BWRC) summer retreat, May 31, 2007, published in ICC conference, July 2007] proposed a search for the highest amplitude peak over the frequency from the wideband spectrum with a low resolution, high-speed analog to digital converter ADC and correlator. This proposal then cancels the result from the original signal before a second digital conversion that uses also the high-speed, low resolution ADC. It appears to the inventors that the dynamic range for the second ADC is significantly reduced in this proposal, though the wide-band signal may still be converted completely.
What is needed in the art is a way to find those free areas that may be located anywhere among the wideband spectrum at various times with low power requirements and high confidence level.